All Reed freshman are required to take Humanities 110.

• Statistics within the math department
• Classes:
  • Intro stats
  • Year-long junior level prob & math stats sequence
  • Applied/methods classes in other departments
• New class: MATH241 Case Studies in Statistical Analysis

Prereqs

Only intro stats and some exposure to R

Syllabus

• 5 biweekly mini-reports submitted in R Markdown: reproducible research
• Term project: both report and 20 min oral
• In-class participation

18 students, mostly juniors and seniors.

ASA's GAISE Reports

• Use real data.
• Stress conceptual understanding, rather than mere knowledge of procedures.
• Foster active learning in the classroom.
• Use technology for developing conceptual understanding and analyzing data.

• Messy data needing cleaning, from potentially disparate sources
• Bottom-up: Let questions/data motivate the statistical methodology, rather than vice-versa
• Discussions in class
• Focus on the entire analysis pipeline: article in Nature
• Lean on R heavily

• Key: Forget base R
• How? The Hadleyverse of packages by Hadley Wickham.
• In particular
  • dplyr package for data wrangling/manipulation
  • ggplot2 package for data visualization

Features

• Data manipulation is performed using verbs
• The pipe %>% command. For example: say you want to apply functions h() then g() then f() on data x. You can do
  • f(g(h(x))) OR
  • h(x) %>% g() %>% f()

Info on all domestic flights leaving Houston (IAH) in 2011:

• flights: info on all 227,496 flights
• planes: information on all 2853 airplanes

What are the top 5 carriers using the oldest planes (averaged over all flights)?

The flights dataset:

The planes dataset:

The following sequence of verbs wrangle/manipulate the data:

left_join(flights, planes, by='plane') %>%
  select(carrier, plane, year) %>%
  mutate(age = 2011 - year) %>%
  group_by(carrier) %>%
  summarise(avg_age = mean(age)) %>%
  arrange(desc(avg_age)) %>%
  top_n(5)

A statistical graphic consists of a mapping of data variables to aesthetic attributes of geometric objects that we can observe.

ggplot2 allows us to construct graphics in a modular fashion by specifying these components.

• Sample of 10% of San Francisco OkCupid users in June 2012 (\(n=5995\))
• 40.2% of the sample was female
  
• Use logistic regression to predict gender

Best predictors have distinct differences (in gender) in large segments of the population.

All 222,540 songs played on the Reed pool hall jukebox from 2003-2009 c/o Noah Pepper '09

quandl.com is a great source for economic data

• Baby Name Popularity in US
• Portland Crime
• Insect Abundance

• You hear this a lot:
  • Statistician: Hi, I'm a statistician.
  • Non-statistician: Statistics? I hated that class!

• You'll never hear this:
  • Statistician: Hi, my work involves a lot of data visualization.
  • Non-statistician: Data visualization? I hate that stuff!

• Data visualization is a backdoor way to get students interested in statistics.
• Prez from Season 4 of "The Wire":
• 

This is the only stats class many will take.

• Get them looking at, manipulating, and visualizing data QUICK
• Better integration of lectures and labs
• Flipped-classroom
  • Lab exercises at home
  • Problem solving/debugging and discussion in class

• A class focused on the data first, methods second, using only open-source tools.
• Rich Majerus wrote "Why should students at a small liberal arts college learn R?"
• New tools like Datacamp are increasing the ratio: \[\frac{\mbox{Payoff from learning R}}{\mbox{Startup costs}}\]
• Data visualization is a gateway drug for statistics
• Developing skills and intuition takes time. Instructor attention and feedback are crucial.
• Interactivity boosts student interest

• Presentation slides: RPubs.com/rudeboybert
• Code and (non-private) data for class: github.com/rudeboybert/MATH241
• 17 out of 18 final projects data & code